Some current studies have found that workers at many companies spend a significant amount of their time searching for information. A significant number of those workers also report that they find it very difficult to locate information that is required to do their jobs on their internal network systems (such as intranets). Assisting these types of people in accessing information (particularly at an enterprise level) is a challenging issue which many have attempted to address with conventional information retrieval techniques.
However, some conventional information retrieval techniques are not optimally suited to the job. For instance, workers often require not only general search capabilities, but also the capability to search for specific types of information, such as proper names, time schedules, etc.
One current approach to information retrieval is referred to as question answering. the methods used in implementing some current question answering systems are not normally developed to answer questions (or provide information) on a specific type of factoid, and thus, they are not tuned for the type. As a result, question answering systems do not perform well when searching for those types of factoids. Further, question answering systems are often relatively slow, because it is difficult to generate an index for them.
Another type of current information retrieval is known as document retrieval, which is conducted on the basis of a relevance measure that indicates the relevance of a set of documents to queries. Passages are sometimes retrieved, instead of entire documents, for ease of information access. The documents or passages often do not necessarily contain a specific type of information that was requested by the input query.
The discussion above is merely provided for general background information and is not intended to be used as an aid in determining the scope of the claimed subject matter.